Abstract
The analysis of the movement of people in a shopping area with the aim of improving marketing is an important research topic. Many conventional methods are dependent on the density of people in the area, which is easily estimated by counting the people entering or exiting the area. However, a high density does not always mean an increase in activity, as certain people are simply passing the area at a given time. The primary goal of this study was to introduce a set of indicators for measuring the bustle of the area, which we call “Nigiwai,” from pedestrian movement by using an analogy from classical kinematics. Such indicators can be used to measure the impact of promotional events and to optimize the design of the area. Our novel indicators were evaluated with simulated pedestrian scenarios and were demonstrated to distinguish shopping scenarios from those in which people move around without shopping successfully, even when the latter scenarios had much higher densities. The indicators were computed solely from the pedestrian trajectory, which can easily be obtained from ordinary sensors using deep learning-based techniques. As a demonstration with real data, we applied our method to a video of a street and provided a visualization of the indicators.
Highlights
The analysis of pedestrian behavior has become an active research topic
Our indicators are computed solely from the pedestrian trajectories, which can be obtained with surveillance cameras
The proposed method uses both the distances and relative velocities between agents, which enables the finer structures of the pedestrian activities to be captured
Summary
The analysis of pedestrian behavior has become an active research topic. In addition to traditional qualitative methods that rely on factors such as inquiry, quantitative methods have become increasingly prevalent owing to the advances in the collection and processing of big data (see Section II). Quantitative metrics offer a measure for assessing or predicting the effect of a marketing strategy, such as a promotional event. By using these metrics, the arrangements of shops and paths can be optimized to increase the activity of shoppers. An effective evaluation indicator for shopper activity is required to achieve these goals. The sales data or inquiry surveys of shoppers may provide substantial information, these are usually difficult to obtain.
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